Phase 3: Advanced Concepts

You’ve built simple agents. Now it’s time to unlock multi-agent systems, add memory, and prepare your agents for real-world deployment.

🤖 Step 7: Multi-Agent Systems

• Create specialized agents (e.g., Researcher, Writer, Editor)

• Build workflows where agents talk to each other

• Assign different tasks, goals, and memory to each role

• Handle overlaps, task delegation, and communication errors

You’re now simulating real teams — with autonomous digital roles.

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🧠 Step 8: Add Memory & State

• Track past interactions (conversation memory)

• Store user preferences or long-term context

• Connect to knowledge bases or vector stores

• Let your agent “remember” decisions across sessions

State = context. Context = intelligence.

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🧑‍💼 Step 9: Make It Production Ready

• Add logging to monitor performance

• Track cost per run and API usage

• Apply rate limiting and error handling

• Package your agent with Docker or deploy to cloud platforms

Stability, monitoring, and cost control make your agent usable at scale.

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⏱️ Daily commitment: 1–2 hours 📈 Success key: Build something every week, no matter how small